CoChat
Sign Up
Cited by 41Cancer, Hypoxia, and MetabolismMetabolism, Diabetes, and CancerGenetics, Aging, and Longevity in Model Organisms

The DOI matches its Crossref record; 256 of the 256 references it cites were found in a registry or an index.

Metabolic reprogramming: a bridge between aging and tumorigenesis

Open access
Drapela, Stanislav, Ilter, Didem, Gomes, Ana P.·2022·Molecular Oncology
DOI 10.1002/1878-0261.13261PMC PMC9490145
Open this paper in CoChat — free accountOpen PDF

Abstract

Aging is the most robust risk factor for cancer development, with more than 60% of cancers occurring in those aged 60 and above. However, how aging and tumorigenesis are intertwined is poorly understood and a matter of significant debate. Metabolic changes are hallmarks of both aging and tumorigenesis. The deleterious consequences of aging include dysfunctional cellular processes, the build-up of metabolic byproducts and waste molecules in circulation and within tissues, and stiffer connective tissues that impede blood flow and oxygenation. Collectively, these age-driven changes lead to metabolic reprogramming in different cell types of a given tissue that significantly affects their cellular functions. Here, we put forward the idea that metabolic changes that happen during aging help create a favorable environment for tumorigenesis. We review parallels in metabolic changes that happen during aging and how these changes function both as adaptive mechanisms that enable the development of malignant phenotypes in a cell-autonomous manner and as mechanisms that suppress immune surveillance, collectively creating the perfect environment for cancers to thrive. Hence, antiaging therapeutic strategies that target the metabolic reprogramming that occurs as we age might provide new opportunities to prevent cancer initiation and/or improve responses to standard-of-care anticancer therapies.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/1878-0261.13261

Cites

256 of 256 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Protumorigenic effects of aging‐associated metabolism in the epithelium. Aging promotes metabolic and redox rewiring, including an increase in ROS and the induction of a Warburg‐like metabolism, which leads to the activation of protumorigenic and proliferation controlling signaling pathways PI3K/AKT/mTOR, p38, JNK, and ERK, and the upregulation of protumorigenic transcription factors such as HIF‐1α, NRF2 or NF‐kB. On the other hand, aging also leads to the suppression of antitumorigenic pathways, including the inhibition of sirtuins via a decrease in NAD+. Together these age‐induced alterations create a metabolic environment in aged epithelial cells that empowers carcinogenesis. ERK, extracellular signal‐regulated kinase; HIF‐1 α, hypoxia‐inducible factor 1α; IGF‐1, insulin‐like growth factor 1; JNK, c‐Jun N‐terminal kinase; NAD, nicotinamide adenine dinucleotide; NF‐kB, nuclear factor‐kappa B; NRF2, nuclear factor erythroid 2‐related factor 2; OXPHOS, oxidative phosphorylation; p38, p38 mitogen‐activated protein kinase; PI3K/Akt/mTOR, phosphoinositide 3‐kinases/protein kinase B/mechanistic target of rapamycin; ROS, reactive oxygen species.
Fig. 1 Protumorigenic effects of aging‐associated metabolism in the epithelium. Aging promotes metabolic and redox rewiring, including an increase in ROS and the induction of a Warburg‐like metabolism, which leads to the activation of protumorigenic and proliferation controlling signaling pathways PI3K/AKT/mTOR, p38, JNK, and ERK, and the upregulation of protumorigenic transcription factors such as HIF‐1α, NRF2 or NF‐kB. On the other hand, aging also leads to the suppression of antitumorigenic pathways, including the inhibition of sirtuins via a decrease in NAD+. Together these age‐induced alterations create a metabolic environment in aged epithelial cells that empowers carcinogenesis. ERK, extracellular signal‐regulated kinase; HIF‐1 α, hypoxia‐inducible factor 1α; IGF‐1, insulin‐like growth factor 1; JNK, c‐Jun N‐terminal kinase; NAD, nicotinamide adenine dinucleotide; NF‐kB, nuclear factor‐kappa B; NRF2, nuclear factor erythroid 2‐related factor 2; OXPHOS, oxidative phosphorylation; p38, p38 mitogen‐activated protein kinase; PI3K/Akt/mTOR, phosphoinositide 3‐kinases/protein kinase B/mechanistic target of rapamycin; ROS, reactive oxygen species.CC BY · PubMed Central
Fig. 2 Aging‐induced metabolic suppression of host defenses. Age‐induced metabolic alterations shape both innate and adaptive immunity resulting in a decline in immune cell activation and proper immune responses. Aging promotes a global decline in NAD+ within the immune compartment due to an increase in the expression of NADase CD38 leading to a decline in cytotoxic effector activity and the induction of an inflammatory state. The decline in glutamine and ɑ‐KG availability with age further negatively impacts the function and differentiation of T cells by limiting substrate availability for TCA anaplerosis and redox reactions. The age‐induced decline in spermidine inhibits autophagy in T cells and disrupts the homeostatic differentiation of CD4+ T cells into specific subsets. On the other hand, aging also induces lactate production and promotes acidification; this acidification reduces the activity of NFAT and IFN‐γ in T cells and NK cells inhibiting their cytotoxic ability and induces protumorigenic M2‐like polarization of macrophages via stabilization of HIF‐1α and induction of Arg1 expression. Similarly, age‐induced elevation in spermine levels favors polarization towards a protumorigenic M2 macrophage phenotype, both dampening the immune response. In addition, lactate contributes to immunosuppression by promoting an activation of Treg phenotype of CD4+ T cells through NF‐kB and FoxP3 activity. This phenomenon can also be controlled by the age‐induced increase in kynurenine, which blocks the cytotoxic activity of T and NK cells. Advanced age might also cause a shift in microbiome composition affecting SCFAs in old hosts and thereby influence antitumor immunity. SCFAs have been shown to regulate innate immune cells via decreasing the secretion of proinflammatory cytokines by macrophages. On the other hand, SCFAs tend to enhance the polarization effects set by the cytokine milieus present at the time of T‐cell priming and differentiation. Green and red arrows indicate increased or decreased level, respectively. ɑ‐KG, α‐ketoglutarate; Arg1, arginase 1; CD38, cluster of differentiation 38; FoxP3, forkhead box P3; HIF‐1 α, hypoxia‐inducible factor 1α; INF‐γ, interferon‐gamma; M1MΦ, M1‐polarized macrophages; M2MΦ, M2‐polarized macrophages; mTORC1, mechanistic target of rapamycin complex 1; NAD, nicotinamide adenine dinucleotide; NFAT, nuclear factor of activated T cells; NF‐kB, nuclear factor‐kappa B; NK cell, natural killer cell; p300, histone acetyltransferase p300; SCFAs, short‐chain fatty acids; TCA, tricarboxylic acid; TFEB, transcription factor EB; Treg, regulatory T. [Colour figure can be viewed at wileyonlinelibrary.com]
Fig. 2 Aging‐induced metabolic suppression of host defenses. Age‐induced metabolic alterations shape both innate and adaptive immunity resulting in a decline in immune cell activation and proper immune responses. Aging promotes a global decline in NAD+ within the immune compartment due to an increase in the expression of NADase CD38 leading to a decline in cytotoxic effector activity and the induction of an inflammatory state. The decline in glutamine and ɑ‐KG availability with age further negatively impacts the function and differentiation of T cells by limiting substrate availability for TCA anaplerosis and redox reactions. The age‐induced decline in spermidine inhibits autophagy in T cells and disrupts the homeostatic differentiation of CD4+ T cells into specific subsets. On the other hand, aging also induces lactate production and promotes acidification; this acidification reduces the activity of NFAT and IFN‐γ in T cells and NK cells inhibiting their cytotoxic ability and induces protumorigenic M2‐like polarization of macrophages via stabilization of HIF‐1α and induction of Arg1 expression. Similarly, age‐induced elevation in spermine levels favors polarization towards a protumorigenic M2 macrophage phenotype, both dampening the immune response. In addition, lactate contributes to immunosuppression by promoting an activation of Treg phenotype of CD4+ T cells through NF‐kB and FoxP3 activity. This phenomenon can also be controlled by the age‐induced increase in kynurenine, which blocks the cytotoxic activity of T and NK cells. Advanced age might also cause a shift in microbiome composition affecting SCFAs in old hosts and thereby influence antitumor immunity. SCFAs have been shown to regulate innate immune cells via decreasing the secretion of proinflammatory cytokines by macrophages. On the other hand, SCFAs tend to enhance the polarization effects set by the cytokine milieus present at the time of T‐cell priming and differentiation. Green and red arrows indicate increased or decreased level, respectively. ɑ‐KG, α‐ketoglutarate; Arg1, arginase 1; CD38, cluster of differentiation 38; FoxP3, forkhead box P3; HIF‐1 α, hypoxia‐inducible factor 1α; INF‐γ, interferon‐gamma; M1MΦ, M1‐polarized macrophages; M2MΦ, M2‐polarized macrophages; mTORC1, mechanistic target of rapamycin complex 1; NAD, nicotinamide adenine dinucleotide; NFAT, nuclear factor of activated T cells; NF‐kB, nuclear factor‐kappa B; NK cell, natural killer cell; p300, histone acetyltransferase p300; SCFAs, short‐chain fatty acids; TCA, tricarboxylic acid; TFEB, transcription factor EB; Treg, regulatory T. [Colour figure can be viewed at wileyonlinelibrary.com]CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

1 retracted

Show all 256 references

Cited by

Sorted by citations

Related

See all

Metadata

Authors
Drapela, S., Ilter, D., & Gomes, A. P.
Affiliations
  • Department of Molecular Oncology H. Lee Moffit Cancer Center & Research Institute Tampa FL USA
  • Moffitt Cancer Center (US)
Corresponding author
Gomes, Ana P.
ORCID
Venue
Molecular Oncology
Publisher
Wiley
Published
2022-06-19
Volume
16
Issue
18
Pages
3295-3318
ISSN
  • 1574-7891 (ISSN-L)
  • 1878-0261
DOI
10.1002/1878-0261.13261
PMC
PMC9490145
OpenAlex
W4281620894
Cited by
41
References
256
Citations by year
2026: 11 · 2025: 18 · 2024: 5 · 2023: 4 · 2022: 3
FWCI
0.91
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecular Oncology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • American Lung Association
  • Florida Breast Cancer Foundation
  • National Cancer Institute (R00CA218686)
  • NIH Office of the Director (DP2 AG0776980)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolism, Diabetes, and Cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
Keywords
metabolic reprogramming, aging, carcinogenesis, cellular senescence, immune surveillance, cancer prevention, tumor microenvironment, metabolic waste accumulation
MeSH terms
Cell Transformation, Neoplastic, Humans, Neoplasms

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review